5 papers
Vela: Scaling Vision-Language-Action Models with Adaptive Action Curve Parametrization
Yifan Li, Jiaxu Wang, Dongming Wu +4
Most vision-language-action models represent future motion as fixed-rate action chunks, tying temporal resolution and prediction horizon to a fixed output budget. This pointwise re…
StructRL: Structured Action-Space Exploration for Flow-Based VLAs
Jiarui Yang, Bin Zhu, Jingjing Chen +4
Flow-based Vision-Language-Action (VLA) models are now widely used for continuous robotic manipulation, and online reinforcement learning (RL) is emerging as a key technique for ad…
Vid2WAM: Distilling Video Diffusion Priors into World Action Models
Chenhao Qiu, Ruixiang Wang, Runyi Zhao +7
World Action Models (WAMs) improve robot policy learning by jointly modeling future visual dynamics and actions. However, their scalability and generalization remain constrained by…
-WM: A Unified Video-Action World Model for Robotic Manipulation
Pengfei Zhou, Shengcong Chen, Di Chen +17
Robotic manipulation requires models that generate executable actions while anticipating and evaluating their future consequences before physical execution. We present -World…
Say, Dream, and Act: Learning Video World Models for Instruction-Driven Robot Manipulation
Songen Gu, Yunuo Cai, Tianyu Wang +2
Robotic manipulation requires anticipating how the environment evolves in response to actions, yet most existing systems lack this predictive capability, often resulting in errors…